Nailong Wu

Papers

Total Citations

124

H-Index

About

Nailong Wu is a leading researcher in underwater robotics, specializing in the modeling, identification, and robust control of complex-shaped autonomous underwater vehicles (AUVs). His work addresses the fundamental challenge of accurately representing the nonlinear dynamics of unconventional underwater platforms, which is critical for reliable autonomous operations in unpredictable marine environments. Wu’s most influential contribution, his 2015 paper on modeling a complex-shaped underwater vehicle for robust control schemes, has garnered 90 citations, establishing a foundational framework for designing control systems that can handle hydrodynamic uncertainties. He further advanced the field by pioneering the use of symbolic regression for parametric identification and structure searching of AUV models, a 2016 study cited 34 times that enables automated discovery of optimal model architectures from empirical data. This innovative approach reduces reliance on manual tuning and enhances model fidelity for real-world applications. Wu’s research is instrumental in bridging the gap between theoretical control design and practical deployment, making him a key figure in the development of next-generation underwater vehicles for exploration, defense, and environmental monitoring.